2023/08/11 by Yuto Nishida, Nishida, Yuto, Sahil Bhatia +9
Computer Science · Decision Sciences · #Parallel Computing and Optimization Techniques #Scientific Computing and Data Management #Embedded Systems Design Techniques
paper · pdf · doi:10.48550/arxiv.2308.06410
DSLs and hardware accelerators have proven to be very effective in optimizing computationally expensive workloads. In this paper, we propose a solution to the challenge of manually rewriting legacy or unoptimized code in domain-specific languages and hardware accelerators. We introduce an approach that integrates two open-source tools: Metalift, a code translation framework, and Gemmini, a DNN accelerator generator. The integration of these two tools offers significant benefits, including simplified workflows for developers to run legacy code on Gemmini generated accelerators and a streamlined programming stack for Gemmini that reduces the effort required to add new instructions. This paper provides details on this integration and its potential to simplify and optimize computationally expensive workloads.